A recommendation method applied to a terminal includes a rule platform with system-level permission, the rule platform is configured to save system resources and remind a user of a function of an application. The rule platform obtains a first event and a first rule related to the first event from a rule base. The rule platform includes the rule base including a rule and each rule includes a condition. The rule platform updates a matching status of a first condition corresponding to the first event in the first rule The terminal displays a recommendation result corresponding to the first rule when a matching status of each condition in the first rule indicates that the matching is successful. The first rule is one of the rule related to the first event.
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1. A recommendation method, applied to a terminal comprising a rule platform having a system-level permission, wherein the recommendation method comprises: obtaining, by the rule platform, a first event; obtaining, by the rule platform, a first rule related to the first event from a rule base, wherein the rule platform comprises the rule base comprising a plurality of rules, wherein each of the rules comprises a condition, and wherein the first rule comprises a first condition and a second condition related to a user portrait; updating, by the rule platform, a first matching status of the first condition corresponding to the first event; updating, by the rule platform, a second matching status of the second condition based on the user portrait; displaying, by the terminal, a recommendation result corresponding to the first rule when the first matching status and the second matching status in the first rule indicates that matching is successful; periodically sending, by the terminal, a query request to a cloud server, wherein the query request queries whether the first rule is updated; receiving, by the terminal, an updated rule from the cloud server; and updating, by the terminal, the first rule related to the updated rule in the rule base.
This invention relates to a recommendation system for terminals, such as smartphones or other devices, that dynamically generates personalized recommendations based on user behavior and system events. The system addresses the challenge of providing relevant recommendations by leveraging a rule-based approach that combines real-time event detection with user-specific data. The terminal includes a rule platform with system-level permissions, which monitors events and applies predefined rules stored in a rule base. Each rule contains conditions, including one related to a user portrait (a profile of user preferences or behavior). When an event occurs, the platform checks if the event matches the rule's conditions. If both the event condition and the user portrait condition are satisfied, the terminal displays a recommendation tied to that rule. The system also supports dynamic updates. The terminal periodically queries a cloud server to check for rule updates. If an updated rule is available, the terminal downloads and replaces the existing rule in the rule base, ensuring recommendations remain current. This approach allows for centralized management of rules while maintaining real-time responsiveness on the device. The invention improves recommendation accuracy by combining contextual events with user-specific data, while also enabling seamless updates without manual intervention.
2. The recommendation method of claim 1 , wherein before obtaining the first rule related to the first event, the recommendation method further comprises: receiving, by the rule platform, the first rule from a first application; and storing, by the rule platform, the first rule to the rule base.
This invention relates to a recommendation system that dynamically generates recommendations based on event-triggered rules. The system addresses the challenge of providing personalized and context-aware recommendations by leveraging a rule-based approach, where rules are dynamically updated and applied in response to specific events. The system includes a rule platform that receives and stores rules from various applications. These rules are associated with specific events and define actions or recommendations to be taken when those events occur. For example, a rule may specify that when a user performs a particular action (e.g., viewing a product), a recommendation (e.g., suggesting a related product) should be generated. The rule platform maintains a rule base where these rules are stored for retrieval and application. When an event occurs, the system obtains the relevant rule from the rule base and applies it to generate a recommendation. The rules can be dynamically updated or modified, allowing the system to adapt to changing conditions or user behavior. This ensures that recommendations remain relevant and personalized over time. The system may also include mechanisms to validate or prioritize rules, ensuring that the most appropriate recommendation is selected when multiple rules apply to a single event. The overall approach improves the accuracy and timeliness of recommendations in dynamic environments.
3. The recommendation method of claim 2 , further comprising: sending, by the rule platform, the recommendation result to a second application; and displaying, by the second application, the recommendation result.
This invention relates to a recommendation system that generates and delivers personalized recommendations to users. The system addresses the challenge of providing relevant suggestions in a scalable and efficient manner by leveraging a rule-based platform to process user data and generate tailored recommendations. The rule platform applies predefined rules to analyze user behavior, preferences, or contextual data to produce a recommendation result. This result is then transmitted to a second application, which displays the recommendation to the user. The system ensures that recommendations are dynamically generated and presented in a user-friendly manner, enhancing decision-making processes in applications such as e-commerce, content streaming, or personalized services. The method improves upon traditional recommendation systems by integrating a rule-based approach with seamless delivery mechanisms, ensuring real-time and context-aware suggestions. The invention focuses on the technical aspects of generating, transmitting, and displaying recommendations, optimizing user engagement and system performance.
4. The recommendation method of claim 2 , further comprising: storing, by the rule platform, the recommendation result; obtaining, by a second application, the recommendation result from the rule platform; and displaying, by the second application, the recommendation result.
This invention relates to a recommendation system that generates and shares recommendations across multiple applications. The system addresses the challenge of providing consistent and personalized recommendations to users across different applications while maintaining centralized control over recommendation logic. The core method involves a rule platform that generates a recommendation result based on predefined rules and user data. The rule platform stores this recommendation result in a centralized location. A second application, distinct from the first application that triggered the recommendation, retrieves the stored recommendation result from the rule platform. The second application then displays the recommendation result to the user, ensuring that the same recommendation is accessible across multiple applications without redundant processing. This approach allows for consistent recommendations while reducing computational overhead by avoiding repeated generation of the same recommendation. The system is particularly useful in environments where multiple applications need to provide synchronized recommendations to users, such as e-commerce platforms, content streaming services, or personalized marketing systems. The centralized storage and retrieval mechanism ensures that recommendations remain up-to-date and consistent across all applications.
5. The recommendation method of claim 1 , wherein before displaying the recommendation result, the recommendation method further comprises: obtaining, by the rule platform, a current user portrait from a user portrait platform of the terminal; and updating, by the rule platform, the second matching status of the second condition based on the current user portrait.
This invention relates to personalized recommendation systems that dynamically adjust recommendations based on real-time user data. The system addresses the challenge of providing relevant recommendations by continuously updating user profiles and refining recommendation logic in response to changing user behavior and preferences. The method involves a rule platform that generates recommendations by evaluating conditions associated with recommendation rules. Before displaying a recommendation, the system retrieves a current user portrait—a dynamic profile of the user's attributes, preferences, and behavior—from a user portrait platform on the user's terminal. The rule platform then updates the matching status of a second condition in the recommendation rule based on this real-time user data. This ensures that the recommendation logic adapts to the user's current context, improving relevance and accuracy. The system may also include a rule engine that processes recommendation rules, a rule storage platform that stores these rules, and a user portrait platform that maintains and updates user profiles. The rule platform interacts with these components to dynamically adjust recommendations, ensuring they align with the user's latest preferences and behavior. This approach enhances recommendation accuracy by incorporating real-time user data into the decision-making process.
6. The recommendation method of claim 1 , further comprising displaying, by the terminal, the recommendation result corresponding to the first rule when matching statuses of all conditions in the first rule and a second rule indicate that matching is successful and a first priority of the first rule is higher than a second priority of the second rule, wherein the second rule is related to the first event.
This invention relates to a recommendation system that processes event-based rules to generate and display recommendations. The system addresses the challenge of selecting the most relevant recommendation when multiple rules match a given event, ensuring the highest-priority rule is prioritized. The method involves a terminal that receives an event and evaluates multiple rules associated with that event. Each rule contains conditions that must be met for the rule to apply. When multiple rules match the event, the system compares their priorities. If the first rule has a higher priority than the second rule, the terminal displays the recommendation result associated with the first rule. This ensures that only the most relevant recommendation is shown to the user, improving decision-making efficiency. The system dynamically assesses rule conditions and priorities, allowing for flexible and context-aware recommendations. By prioritizing higher-priority rules, it avoids conflicts and ensures consistency in recommendation outputs. This approach is particularly useful in applications where multiple factors influence recommendations, such as e-commerce, personalized content delivery, or decision support systems. The method enhances user experience by providing the most appropriate recommendation based on predefined rule hierarchies.
7. The recommendation method of claim 1 , wherein the rule platform further comprises an interface layer and a rule engine, and wherein the recommendation method further comprises: obtaining, by the interface layer, the first event; obtaining, by a rule status processor of the rule engine and from the rule base, the first rule related to the first event; updating, by the rule status processor, the first matching status of the first condition corresponding to the first event in the first rule related to the first event; storing, by a personal knowledge base of the rule engine, the first event and the first matching status of the first condition in the first rule related to the first event; obtaining, by the personal knowledge base, a current user portrait from a user portrait platform; updating, by the personal knowledge base, the second matching status of the second condition based on the current user portrait; storing, by a recommendation result candidate set of the rule engine, the recommendation result corresponding to the first rule when the first matching status and the second matching status in the first rule indicates that the matching is successful; and displaying, by a graphical user interface, the recommendation result.
This invention relates to a recommendation system that uses a rule-based platform to generate personalized recommendations. The system addresses the challenge of dynamically adapting recommendations based on real-time events and user profiles. The rule platform includes an interface layer and a rule engine. The interface layer receives a first event, such as user interaction or system-generated data. The rule engine contains a rule status processor and a personal knowledge base. The rule status processor retrieves a first rule from a rule base that corresponds to the first event and updates the matching status of a first condition in the rule. The personal knowledge base stores the event and the updated matching status. It also retrieves a current user portrait, which represents the user's preferences or behavior, from a user portrait platform. The personal knowledge base then updates the matching status of a second condition in the rule based on the user portrait. If both conditions in the rule are satisfied, the recommendation result associated with the rule is stored in a recommendation result candidate set. Finally, the recommendation is displayed to the user through a graphical user interface. This approach ensures that recommendations are tailored to both the current event and the user's profile, improving relevance and personalization.
8. A terminal comprising: a rule platform comprising: a system-level permission; an interface layer configured to obtain a first event; and a rule engine coupled to the interface layer and comprising: a personal knowledge base configured to store the first event; a rule base comprising a plurality of rules, wherein each of the rules comprises a condition; and a rule status processor coupled to the personal knowledge base and the rule base and, configured to: obtain a first rule related to the first event from the rule base, wherein the first rule comprises a first condition and a second condition related to a user portrait; update a first matching status of a first condition corresponding to the first event in the first rule related to the first event; update a second matching status of the second condition based on the user portrait; record the matching status in the personal knowledge base; and output a recommendation result corresponding to the first rule when the first matching status and the second matching status in the first rule indicates that matching is successful, wherein the personal knowledge base is further configured to store the matching status and the second matching status in the first rule related to the first event, and wherein the rule base is configured to: periodically send a query request to a cloud server, wherein the query request queries whether the first rule is updated; receive, through the interface layer, an updated rule from the cloud server; and update the first rule related to the updated rule in the rule base; and a graphical user interface coupled to the rule platform and configured to display the recommendation result.
A terminal system is designed to provide personalized recommendations by evaluating events and user profiles against predefined rules. The system includes a rule platform with a system-level permission layer, an interface for capturing events, and a rule engine. The rule engine stores events in a personal knowledge base and applies rules from a rule base, where each rule has conditions related to the event and user characteristics. A rule status processor checks these conditions, updates their matching statuses, and records them. If both conditions are satisfied, the system outputs a recommendation. The rule base periodically checks for updates from a cloud server and applies them to maintain current rules. A graphical user interface displays the recommendation results to the user. This system enables dynamic, context-aware recommendations by combining real-time event data with user-specific profiles and adaptable rules.
9. The terminal of claim 8 , wherein the interface layer is further configured to: receive the first rule from a first application; and store the first rule to the rule base.
This invention relates to a terminal device with an interface layer that manages communication between applications and a rule base. The problem addressed is the need for efficient rule management in terminals where multiple applications interact with shared resources or services. The terminal includes an interface layer that facilitates communication between applications and a rule base, which stores rules governing system behavior. The interface layer is configured to receive a first rule from a first application and store it in the rule base. This allows applications to dynamically update rules without direct access to the rule base, ensuring controlled and secure rule management. The terminal may also include a rule base manager that processes and enforces rules, ensuring consistency across applications. The interface layer acts as an intermediary, preventing direct access to the rule base by applications, thereby maintaining system integrity. This approach improves flexibility and security in rule-based systems by centralizing rule storage and access control. The invention is particularly useful in environments where multiple applications must adhere to shared rules, such as in networked devices or embedded systems.
10. The terminal of claim 9 , wherein the rule status processor is further configured to send the recommendation result to a second application, and wherein the graphical user interface is further configured to display the recommendation result using the second application.
This invention relates to a terminal device with enhanced rule-based processing and recommendation display capabilities. The terminal includes a rule status processor that evaluates predefined rules to generate recommendation results. These results are then transmitted to a second application, which is distinct from the primary application handling the initial rule processing. The terminal also features a graphical user interface (GUI) that displays the recommendation results through the second application, ensuring that users receive actionable insights in a separate, dedicated interface. This separation allows for better organization and clarity in presenting recommendations, improving user experience and decision-making efficiency. The system is particularly useful in environments where multiple applications interact, such as enterprise software, where recommendations derived from one application need to be displayed in another for seamless workflow integration. The invention addresses the challenge of maintaining clear, actionable recommendations while leveraging multiple applications, ensuring that users can access and act on recommendations without context switching or interface clutter. The rule status processor and GUI work together to streamline the presentation of recommendations, enhancing usability and productivity.
11. The terminal of claim 9 , wherein the rule engine further comprises a recommendation result candidate set, wherein the rule status processor is further configured to output the recommendation result to the recommendation result candidate set, and wherein the graphical user interface is further configured to display the recommendation result obtained by a second application from the recommendation result candidate set.
This invention relates to a terminal device with an enhanced rule engine for generating and displaying recommendation results. The terminal includes a rule engine that processes rules to produce recommendation results, which are then stored in a recommendation result candidate set. A rule status processor within the engine outputs these results to the candidate set, allowing them to be accessed by other applications. The terminal also features a graphical user interface (GUI) that displays recommendation results obtained by a second application from the candidate set. This system enables seamless sharing and presentation of recommendation data across different applications, improving user experience and decision-making efficiency. The rule engine dynamically processes rules to generate actionable insights, which are then made available to multiple applications through the candidate set, ensuring consistent and accessible recommendations. The GUI provides a unified display for these results, enhancing usability and integration across the terminal's applications. This approach addresses the challenge of siloed recommendation data by centralizing results in a shared candidate set, allowing different applications to leverage the same insights without redundant processing. The terminal's architecture supports real-time updates and cross-application consistency, making it suitable for environments requiring coordinated decision support.
12. The terminal of claim 8 , further comprising a user portrait platform, wherein the personal knowledge base is further configured to: obtain a current user portrait from the user portrait platform of the terminal; and update the second matching status of the second condition based on the current user portrait.
This invention relates to a terminal device with an enhanced personal knowledge base system designed to improve user experience by dynamically adapting to user preferences and behaviors. The system addresses the problem of static content recommendations that fail to account for evolving user interests or contextual factors. The terminal includes a personal knowledge base that stores user-specific data and conditions for content matching. The system evaluates these conditions to determine a matching status, which influences how content is presented or recommended to the user. The personal knowledge base can obtain a current user portrait—a profile reflecting the user's attributes, preferences, or behaviors—from a dedicated user portrait platform within the terminal. This portrait is used to update the matching status of conditions, ensuring recommendations remain relevant over time. The system may also include a content matching module that processes the matching status to refine content delivery, and a content display module that presents the matched content to the user. The invention enables real-time personalization by continuously updating user profiles and adjusting content recommendations accordingly.
13. A terminal comprising: a memory configured to store a rule base, wherein the rule base comprises a rule, and wherein each of the rule comprises a condition; a processor coupled to the memory and configured to: obtain a first event; obtain a first rule related to the first event from the rule base, wherein the first rule comprises a first condition and a second condition related to a user portrait; update a first matching status of a first condition corresponding to the first event in the first rule related to the first event; update a second matching status of the second condition based on the user portrait; and output a recommendation result corresponding to the first rule when the first matching status and the second matching status in the first rule indicates that matching is successful; and a display coupled to the processor and the memory and configured to display the recommendation result corresponding to the first rule, wherein the processor is further configured to: periodically send a query request to a cloud server, wherein the query request queries whether the first rule is updated; obtain an updated rule from the cloud server; and update the first rule related to the updated rule in the rule base.
A terminal system is designed to provide personalized recommendations by evaluating events and user profiles against a set of rules. The system includes a memory storing a rule base, where each rule contains conditions that must be met for a recommendation to be triggered. A processor obtains events and retrieves relevant rules from the rule base, checking whether the event and user profile conditions are satisfied. If both conditions are met, the system outputs a recommendation result, which is displayed to the user. The user profile conditions are dynamically updated based on the user's characteristics. Additionally, the terminal periodically checks for updates to the rules by querying a cloud server. If an updated rule is available, the system retrieves and integrates it into the local rule base. This ensures that recommendations remain relevant and aligned with the latest rule sets. The system is particularly useful in applications requiring real-time, personalized decision-making, such as e-commerce, content delivery, or user behavior analysis.
14. The terminal of claim 13 , wherein the processor is further configured to: receive the first rule from a first application; and store the first rule to the rule base.
This invention relates to a terminal device with enhanced rule management capabilities for processing data. The terminal includes a processor configured to execute a rule engine that applies predefined rules to incoming data streams. The rules are stored in a rule base and can be dynamically updated. The processor is further configured to receive a first rule from a first application and store this rule in the rule base. This allows the terminal to adapt its processing logic based on external inputs, enabling flexible and customizable data handling. The rule engine evaluates incoming data against the stored rules to determine actions such as filtering, transforming, or routing the data. The terminal may also include a communication interface for transmitting and receiving data, ensuring seamless integration with other systems. The dynamic rule management system improves efficiency by allowing real-time adjustments to processing logic without requiring hardware modifications. This is particularly useful in environments where data processing requirements change frequently, such as in industrial automation, network security, or IoT applications. The invention ensures that the terminal can adapt to evolving operational needs while maintaining high performance and reliability.
15. The terminal of claim 14 , wherein the processor is further configured to send the recommendation result to a second application, and wherein the display is further configured to display the recommendation result.
This invention relates to a terminal device with enhanced recommendation capabilities, particularly for generating and displaying personalized recommendations based on user data. The terminal includes a processor, a display, and a memory storing a first application and a second application. The processor is configured to execute the first application to collect user data, such as usage patterns, preferences, or contextual information. The processor then processes this data to generate a recommendation result, which may include suggestions for content, services, or actions tailored to the user. The recommendation result is sent to the second application, which may be a different software module or interface within the terminal. The display is configured to present the recommendation result to the user, ensuring the information is accessible and actionable. This system improves user experience by integrating recommendation logic within the terminal, reducing reliance on external servers and enabling real-time, context-aware suggestions. The invention addresses the need for efficient, localized recommendation generation that respects user privacy by processing data on-device. The terminal may further include input devices for user interaction and communication interfaces for data exchange, enhancing its adaptability across various use cases.
16. The terminal of claim 13 , wherein the processor is further configured to send the recommendation result to the memory, wherein the memory is further configured to store the recommendation result, and wherein the display is further configured to: obtain the recommendation result from the memory; and display the recommendation result.
This invention relates to a terminal device with enhanced recommendation functionality, particularly for systems where recommendations are generated and displayed to a user. The problem addressed is the efficient storage and retrieval of recommendation results to ensure timely and accurate display to the user, improving user experience and system responsiveness. The terminal includes a processor, a memory, and a display. The processor generates a recommendation result based on user data or system inputs. The recommendation result is then sent to the memory for storage. The display retrieves the stored recommendation result from the memory and presents it to the user. This ensures that the recommendation is readily available for display without requiring real-time processing, reducing latency and improving system performance. The memory stores the recommendation result in a structured manner, allowing the display to quickly access and present the information when needed. The display may also refresh or update the recommendation result dynamically based on changes in the stored data. This system is particularly useful in applications where recommendations must be displayed promptly, such as in e-commerce, content streaming, or personalized advertising platforms. The invention optimizes the flow of recommendation data, ensuring seamless integration between processing, storage, and display components.
17. The terminal of claim 13 , wherein the processor is further configured to: obtain a current user portrait from a user portrait platform of the terminal; and update the second matching status of the second condition based on the current user portrait.
This invention relates to a terminal device with enhanced user profile-based condition matching. The terminal includes a processor that manages a set of conditions, each with a matching status indicating whether the condition is satisfied. The processor evaluates these conditions based on real-time data, such as user behavior or device state, and updates their matching statuses accordingly. The terminal also includes a display for presenting information related to these conditions, such as notifications or recommendations, when their matching statuses change. A key feature is the ability to obtain a current user portrait—a dynamic profile summarizing user preferences, habits, or attributes—from a user portrait platform integrated into the terminal. The processor uses this portrait to refine the matching status of conditions, ensuring they align with the user's evolving profile. For example, if a condition relates to content recommendations, the user portrait may adjust the matching status based on recent user interactions or preferences. This dynamic adaptation improves the relevance of the terminal's responses to the user's needs. The invention addresses the challenge of static condition evaluation in devices, where predefined rules may not adapt to changing user contexts. By incorporating real-time user portraits, the terminal provides more personalized and context-aware condition matching, enhancing user experience and device functionality.
18. The recommendation method of claim 1 , further comprising obtaining, by the rule platform, the first rule and a second rule related to the first event from the rule base, wherein the first rule and the second rule comprises the first condition.
This invention relates to a recommendation system that dynamically generates recommendations based on event-triggered rules. The system addresses the challenge of providing personalized and context-aware recommendations by leveraging a rule-based approach to process events and conditions in real time. The method involves a rule platform that monitors for a first event, which may be any detectable occurrence such as user actions, system states, or external triggers. When the first event is detected, the rule platform retrieves a first rule and a second rule from a rule base, where both rules are associated with the first event. These rules include a first condition that must be satisfied for the rules to be applied. The rules may also include additional conditions or actions that define how recommendations are generated or modified based on the event and its context. The system evaluates these rules to determine whether the first condition is met, and if so, proceeds to generate or adjust recommendations accordingly. This dynamic rule-based approach allows the system to adapt recommendations based on real-time conditions, improving relevance and personalization. The invention enhances recommendation systems by incorporating flexible, event-driven rule processing to better align recommendations with user needs and system states.
19. The recommendation method of claim 18 , further comprising monitoring, by an interface layer in the rule platform, the first event only once for the first rule and the second rule.
A system and method for event-driven rule processing in a rule platform involves monitoring events to trigger multiple rules without redundant processing. The technology addresses inefficiencies in traditional rule engines where the same event may be processed multiple times for different rules, leading to unnecessary computational overhead. The system includes an interface layer that monitors events and ensures each event is processed only once, even if multiple rules are triggered by that event. This reduces redundant processing and improves system performance. The interface layer acts as a central point for event monitoring, coordinating rule execution to avoid duplicate evaluations of the same event. The method involves detecting an event, determining which rules are triggered by that event, and executing those rules while ensuring the event is only processed once. This approach optimizes resource usage and enhances the scalability of rule-based systems. The system is particularly useful in environments where events are frequent and multiple rules may apply to the same event, such as in financial transaction processing, fraud detection, or real-time analytics. By minimizing redundant event processing, the system improves efficiency and reduces latency in rule-based decision-making systems.
20. The recommendation method of claim 18 , further comprising randomly displaying a recommendation result corresponding to the first rule or the second rule.
This invention relates to recommendation systems, specifically methods for improving recommendation accuracy and user engagement by dynamically adjusting recommendation rules. The problem addressed is the static nature of traditional recommendation systems, which often fail to adapt to changing user preferences or external factors, leading to suboptimal recommendations. The method involves generating recommendation results based on at least two distinct rules, where each rule represents a different recommendation strategy. The first rule may prioritize user preferences, while the second rule could incorporate external factors like trends or contextual data. The system evaluates the performance of these rules over time, tracking metrics such as user interaction rates or satisfaction scores. Based on this performance data, the system dynamically adjusts the weight or priority of each rule to optimize future recommendations. Additionally, the method includes a randomization feature where the system randomly displays recommendation results from either the first or second rule. This ensures that users are exposed to diverse recommendations, preventing bias toward a single rule and allowing the system to gather more comprehensive performance data. The randomization can be controlled or weighted based on historical performance, ensuring that higher-performing rules are still prioritized while maintaining diversity. By continuously adapting the recommendation rules and incorporating randomization, the system improves recommendation relevance and user engagement over time. This approach is particularly useful in dynamic environments where user preferences or external conditions frequently change.
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September 18, 2017
February 8, 2022
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